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Plase answer the following request: Explain what an embedding layer is and its purpose in Machine Learning.
Answer:
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An embedding layer is a type of layer in a neural network that maps input data into a lower dimensional vector representation. It is typically used to map categorical variables or text into numerical vector representations, which allow the network to learn underlying relationships between the inputs and outputs. This can be useful for tasks such as sentiment analysis, sequence labeling, and text classification, as it helps the network to identify relationships between the inputs and outputs and improve the model’s accuracy.